Dynamical systems modeling for structural understanding of social-ecological systems: A primer

A new paper is just out from the CauSES team about dynamical systems modeling!

Dynamical systems modeling (DSM) explores how a system evolves in time when its elements and the relationships between them are known. The basic idea is that the structure of a dynamical system, expressed by coupled differential or difference equations, determines attractors of the system and, in turn, its behavior. This leads to structural understanding that can provide insights into qualitative properties of real systems, including ecological and social-ecological systems (SES).

Fig. 1
Fig. 1 from the publication: (A) Conceptualization of a DSM corresponding to a SES based on case study of collapse of a Baltic cod fishery. (B) Mathematical formalization of the SES using a system of ordinary differential equations (ca, cj, s, denote adult cod, juvenile cod and sprat abundance respectively). (C) Phase portrait of the DSM. The red dot is the initial state.

DSM generally does not aim to make specific quantitative predictions or explain singular events, but to investigate consequences of different assumptions about a system’s structure. SES dynamics and possible causal relationships in SES get revealed through manipulation of individual interactions and observation of their consequences. Structural understanding is therefore particularly valuable for assessing and anticipating the consequences of interventions or shocks and managing transformation toward sustainability.

Taking into account social and ecological dynamics, recognizing that SES may operate on different time scales simultaneously and that achieving an attractor might not be possible or relevant, opens up possibilities for DSM setup and analysis. This also highlights the importance of assumptions and research questions for model results and calls for closer connection between modeling and empirics.

Understanding the potential and limitations of DSM in SES research is important because the well-developed and established framework of DSM provides a common language and helps break down barriers to shared understanding and dialog within multidisciplinary teams. In this primer we introduce the basic concepts, methods, and possible insights from DSM.

Our target audience are both beginners in DSM and modelers who use other model types, both in ecology and SES research.

Highlights from the paper Dynamical systems modeling for structural understanding of social-ecological systems: A primer:

  • Complex temporal dynamics of human-nature interactions is one of the greatest challenges for understanding and managing social-ecological systems (SES).
  • Dynamical systems modeling (DSM) could provide the necessary theoretical framework for future research and help shape our understanding and management of SES.
  • Shifting research focus from equilibrium thinking and asymptotic dynamics to out-of-equilibrium states and transient dynamics could offer alternative explanations for observed phenomena in SES.
  • Combining DSM with empirical research methods and agent based modeling can help overcome some limitations of DSM, such as relying on simplified assumptions.

Reference: Radosavljevic, S., Banitz, T., Grimm, V., Johansson, L.-G., Lindkvist, E., Schl├╝ter, M., & Ylikoski, P. (2023). Dynamical systems modeling for structural understanding of social-ecological systems: A primer. Ecological Complexity, 56, 101052. https://doi.org/10.1016/j.ecocom.2023.101052

Leave a Reply

Your email address will not be published. Required fields are marked *